Special Education Teachers, Kindergarten
In short: today's best AI models could do about 34% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 66% of the time, stays with people.
Teach academic, social, and life skills to kindergarten students with learning, emotional, or physical disabilities. Includes teachers who specialize and work with students who are blind or have visual impairments; students who are deaf or have hearing impairments; and students with intellectual disabilities.
$65,120 a year (for the broader BLS group this job sits in).
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on1 h
- A person checks AI's work13 h
- Desk work AI can't do yet0 h
- Stays with people26 h
Special Education Teachers, Kindergarten, now: of a 40-hour week, AI could take on 1 hours, 13 hours become checking its work, 0 hours are desk work it can't do yet, and 26 hours stay with people.
The largest pieces: Prepare course objectives and outlines (about 4 h, a person checks); Modify the curriculum (about 3 h, a person checks); Develop and implement strategies (about 2 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 32%
- 3%
- 4%
- 53%
- 9%
Anthropic's data does not cover this job.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 34% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 25%. Today's estimate: 34%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.021% went to this job's tasks in May 2026, the 327th largest of the 447 jobs that showed up at all; 2 of its 29 tasks showed up. Within each of Anthropic's methods, never across a change: 0.025% to 0.029% (released February and March 2025); 0.011% to 0.013% (August 2025 to February 2026); 0.0057% to 0.021% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.025% | 407 of 708 | 5 of 29 |
| Released March 2025 | 0.029% | 365 of 703 | 5 of 29 |
| The week of Aug 4, 2025 (released September 2025) | 0.011% | 446 of 655 | 5 of 29 |
| The week of Nov 13, 2025 (released January 2026) | 0.02% | 389 of 672 | 5 of 29 |
| The week of Feb 5, 2026 (released March 2026) | 0.013% | 463 of 677 | 4 of 29 |
| April 2026 (released June 2026) | 0.0057% | 422 of 434 | 1 of 29 |
| May 2026 (released June 2026) | 0.021% | 327 of 447 | 2 of 29 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 27% of this job's working time as physical work. For 6% of the working time, a robot has been shown doing most of the task somewhere: 6% in a purpose-built cell. 0.06 of 3, the 570th highest of the 923 jobs.
- Not physical 73%
- No robot shown 21%
- In a purpose-built cell 6%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
64% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Instruct in academic subjects, the in-person work, 10%
- Use special education strategies, the in-person work, 7%
- Teach social behavior, the in-person work, 7%
- Develop and implement strategies, the in-person work, 6%
- Set and enforce classroom rules, the in-person work, 5%
- Monitor teachers and assistants, the in-person work, 3%
What becomes checking the machine
31% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 2% is desk work that is small if wrong, which can be handed over with lighter checks.
- Prepare course objectives and outlines, costly if wrong, 10%
- Modify the curriculum, a licensed person signs, 7%
- Develop and implement strategies, a licensed person signs, 4%
- Keep student records, costly if wrong, 3%
- Monitor teachers and assistants, costly if wrong, 2%
- Prepare, give and grade assignments, a licensed person signs, 2%
What to learn
- The conversations. About 57% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Signing off under your license. Some tasks need a licensed, certified or sworn person to do or sign them. The license, and the judgment it stands for, stays with the person.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check or sign: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 32% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 29 tasks from .
| Task | ||||
|---|---|---|---|---|
| Develop or implement strategies to meet the needs of students with a variety of disabilities.Strategies worked out on paper and used in the room.Done hourly or more by most who do it. | 11% | 1.3 h25 min to 3.3 h | In person 60%, documents 40% | 40%Desk part half by now |
| Instruct students with disabilities in academic subjects, using a variety of techniques, such as phonetics, multisensory learning, or repetition to reinforce learning and meet students' varying needs.Teaching with phonetics, multisensory and repetition techniques in the room.Done hourly or more by most who do it. | 10% | 50 min25 min to 1.7 h | In person 100% | Stays with people |
| Prepare objectives, outlines, or other materials for courses of study, following curriculum guidelines or school or state requirements.Objectives and outlines written to the guidelines.Done daily by most who do it. AI observed on this task. | 10% | 1.7 h50 min to 4.2 h | Documents 100% | 100%Half by now |
| Employ special educational strategies or techniques during instruction to improve the development of sensory- and perceptual-motor skills, language, cognition, or memory.Teaching with techniques for sensory, motor, language and memory development.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 50 min17 min to 2.1 h | In person 100% | Stays with people |
| Teach socially acceptable behavior, employing techniques such as behavior modification or positive reinforcement.Behavior teaching with reinforcement techniques in the room.Done hourly or more by most who do it. | 7% | 38 min13 min to 1.3 h | In person 100% | Stays with people |
| Modify the general kindergarten education curriculum for students with disabilities.Adapting the kindergarten curriculum on paper.Done daily by most who do it. | 7% | 1.3 h25 min to 3.3 h | Documents 100% | 99%Half by now |
| Monitor teachers or teacher assistants to ensure adherence to special education program requirements.Watching the program in the rooms, with review behind it.Done daily by most who do it. | 6% | 50 min17 min to 1.7 h | In person 60%, documents 40% | 40%Desk part half by now |
| Establish and enforce rules for behavior and procedures for maintaining order among students.Keeping order in the room.Done hourly or more by most who do it. | 5% | 21 min8 min to 50 min | In person 100% | Stays with people |
| Observe and evaluate students' performance, behavior, social development, and physical health.Watching children in the room, with notes on their progress.Done hourly or more by most who do it. AI observed on this task. | 5% | 25 min13 min to 50 min | In person 70%, documents 30% | 30%Desk part half by now |
| Prepare classrooms with a variety of materials or resources for children to explore, manipulate, or use in learning activities or imaginative play.Setting out materials for the children, with some planning.Done daily by most who do it. Robots: in a purpose-built cell, RightPick 3 (RightHand Robotics) (sold). Anthropic's rating. | 3% | 38 min17 min to 1.7 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Organize and display students' work in a manner appropriate for their perceptual skills.Work organized and put up in the room.Done daily by most who do it. AI observed on this task.Robots: in a purpose-built cell, Ripcord robotic digitization workcell (sold). Anthropic's rating. | 3% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Maintain accurate and complete student records as required by laws, district policies, or administrative regulations.Records kept in the school system as the law requires.Done daily by most who do it. | 3% | 38 min17 min to 1.7 h | Systems 70%, documents 30% | 100%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Special Education Teachers, Elementary School40% now, 40% by 2028
- Special Education Teachers, Middle School40% now, 40% by 2028
- Special Education Teachers, Preschool25% now, 26% by 2028
- Special Education Teachers, Secondary School36% now, 36% by 2028
- Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors66% now, 66% by 2028
- Teaching Assistants, Special Education5% now, 5% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Special Education Teachers, Kindergarten is within reach of AI now?
- An estimated 34% of the working time is within reach of AI models now and 34% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Special Education Teachers, Kindergarten come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Prepare course objectives and outlines (100% of the task's time now); Modify the curriculum (99% of the task's time now); and Develop and implement strategies (40% of the task's time now).
- Which tasks of Special Education Teachers, Kindergarten stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Instruct in academic subjects; Use special education strategies; and Teach social behavior. Together such tasks are about 42% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Special Education Teachers, Kindergarten learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the conversations; signing off under your license; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 64% of the working time stays with people, 31% becomes checking a model's work and 2% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Special Education Teachers, Kindergarten?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.021% went to this job's tasks, the 327th largest share of the 447 jobs that showed up; 2 of its 29 tasks appeared. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Special Education Teachers, Kindergarten?
- Anthropic's robot exposure rating (September 2026) finds 27% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 6% of the working time. Its index is 0.06 of 3. One example: RightPick 3 (RightHand Robotics) for "prepare the classroom with materials". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 29 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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